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CVPR
2006
IEEE

Learning Object Shape: From Drawings to Images

11 years 6 months ago
Learning Object Shape: From Drawings to Images
We consider the important challenge of recognizing a variety of deformable object classes in images. Of fundamental importance and particular difficulty in this setting is the problem of "outlining" an object, rather than simply deciding on its presence or absence. A major obstacle in learning a model that will allow us to address this task is the need for hand-segmented training images. In this paper we present a novel landmark-based, piecewise-linear model of the shape of an object class. We then formulate a learning approach that allows us to learn this model with minimal user supervision. We circumvent the need for hand-segmentation by transferring the shape "essence" of an object from drawings to complex images. We show that our method is able to automatically and effectively learn and localize a variety of object classes.
Gal Elidan, Geremy Heitz, Daphne Koller
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2006
Where CVPR
Authors Gal Elidan, Geremy Heitz, Daphne Koller
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